Disclaimer

The opinions shared here represent those of the contributor themselves and not those of their employers nor that of Big Men On Content as a whole.

To me Content Analytics has always been an intriguing field. When I saw what data mining could do with reporting on metadata stored within their vast databases, I was impressed. Being a believer of the 80% unstructured to 20% structured data in an enterprise, I saw the real power to be if someone could look at all that unstructured content. I used to wonder what could really be done with all that data. A small act in 1999 would make all those capabilities visible to us today. That was the formation of In-Q-Tel.

In-Q-Tel is a private venture capital firm created by request of the Director of Central Intelligence with support of the US Congress. Their goal is to help leverage technical innovation from the private sector for use in the intelligence community. Their press releases even states that they are “a private venture group funded by the Central Intelligence Agency (CIA).” If someone wants to see what possible with metadata and content analytics one only needs to look at their portfolio. For instance, there’s …

(Please note that the list of the companies and the descriptions I’m about to share is all PUBLIC information posted in the portfolio section of In-Q-Tel website and the website’s of the companies they invested in.)

Basis Technology – Basis collects feeds from social media sites like Facebook, Twitter, LinkedIn, and WordPress in 40 different languages. They combine the content and then review not only the semantics but sentiment of each message. They then extrapolate people, places, and products. Finally they present all of this in streamline dashboards.

Cloudera – They offer big data analysis grouping multiple data sources in an organization to develop 360-degree views on their customers. They also offer predictive modeling, telemetry, and time-series processing of that data. They say that the analysis occurs “closer to the disk” to improve the time required to perform complex data analysis.

Digital Reasoning – Their Synthesis product aggregates structure and unstructured data and develops relationships between entities using named entity recognition, time and geographical references.

Narrative Science – Quill uses artificial intelligence engines to extract key facts from data and develop stories. It reviews the content for key facts, relationship, correlations and even inflections to develop a set of facts used to develop the stories. It then uses these facts and relationships to draw conclusions on the stories based on questions asked by the reader.

Netbase – Their product looks at social media sites like Facebook, Pinterest, Twitter, and YouTube to measure brand loyalty based on Likes, Shares, comments, and calculated sentiment.

NovoDynamics – Takes data mining capabilities to the physical world by scanning large volumes on documents in multiple languages. It then indexes the documents and uses pattern recognition to perform data mining and predicative analysis.

Palantir – A knowledge management system that provides single search for enterprise data and performs statistical, geospatial, and relational discovery. Being a knowledge management solution they track the sources of data for any of their analysis.

Platfora – Their product is visual interface tool that performs BI without the need of a data warehouse.

Quantum 4d – Their product performs statistical analysis and develops ontologies and hierarchies on data collections. These are then represented in visual forms.

Visible Technologies – Visible Intelligence is another social media monitoring application that performs analytics on posts.

These ten companies offer viable solutions that are available to the enterprise today. So it’s not really a question of “if” content analytics is a viable in today’s enterprise but more of a question of “what’s next.”